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import gradio as gr |
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import torch |
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from torchvision import transforms |
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model = torch.jit.load("../models/mobilenet.pt") |
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model.eval() |
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transform = transforms.Compose([ |
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transforms.RandomResizedCrop(224), |
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transforms.RandomHorizontalFlip(), |
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transforms.ToTensor(), |
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transforms.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225]) |
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]) |
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CLASSES = ["Ak", "Ala_Idris", "Buzgulu", "Dimnit", "Nazli"] |
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def classify_image(inp): |
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inp = transform(inp).unsqueeze(0) |
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out = model(inp) |
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return CLASSES[out.argmax().item()] |
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iface = gr.Interface(fn=classify_image, |
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inputs=gr.Image(type="pil", label="Input Image"), |
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outputs="text", |
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examples=[ |
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"../data/app_data/ak.png", |
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"../data/app_data/idris.png", |
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"../data/app_data/buzgulu.png", |
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"../data/app_data/dimnit.png", |
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"../data/app_data/nazli.png", |
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]) |
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iface.launch() |
